RL Weekly 36: AlphaZero with a Learned Model achieves SotA in Atari
Por um escritor misterioso
Last updated 10 abril 2025

In this issue, we look at MuZero, DeepMind’s new algorithm that learns a model and achieves AlphaZero performance in Chess, Shogi, and Go and achieves state-of-the-art performance on Atari. We also look at Safety Gym, OpenAI’s new environment suite for safe RL.

PDF) OCAtari: Object-Centric Atari 2600 Reinforcement Learning Environments

deep learning – Severely Theoretical

RL Weekly

PDF) Model-free Reinforcement Learning with Stochastic Reward Stabilization for Recommender Systems

State of AI Report 2023 - Air Street Capital

2008.06495] Joint Policy Search for Multi-agent Collaboration with Imperfect Information

deep learning – Severely Theoretical

Applied Sciences, Free Full-Text

Memory for Lean Reinforcement Learning.pdf

RL Weekly 9: Sample-efficient Near-SOTA Model-based RL, Neural MMO, and Bottlenecks in Deep Q-Learning : r/reinforcementlearning

Mastering Atari Games with Limited Data – arXiv Vanity

RL Weekly 37: Observational Overfitting, Hindsight Credit Assignment, and Procedurally Generated Environment Suite

RL Weekly 9: Sample-efficient Near-SOTA Model-based RL, Neural MMO, and Bottlenecks in Deep Q-Learning
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